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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="preprocessor">#ifndef CAFFE_SYNCEDMEM_HPP_</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="preprocessor">#define CAFFE_SYNCEDMEM_HPP_</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;</div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="preprocessor">#include &lt;cstdlib&gt;</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="preprocessor">#ifdef USE_MKL</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="preprocessor">  #include &quot;mkl.h&quot;</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#endif</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;</div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="preprocessor">#include &quot;caffe/common.hpp&quot;</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;</div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacecaffe.html">caffe</a> {</div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;</div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment">// If CUDA is available and in GPU mode, host memory will be allocated pinned,</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment">// using cudaMallocHost. It avoids dynamic pinning for transfers (DMA).</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment">// The improvement in performance seems negligible in the single GPU case,</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment">// but might be more significant for parallel training. Most importantly,</span></div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment">// it improved stability for large models on many GPUs.</span></div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="keyword">inline</span> <span class="keywordtype">void</span> CaffeMallocHost(<span class="keywordtype">void</span>** ptr, <span class="keywordtype">size_t</span> size, <span class="keywordtype">bool</span>* use_cuda) {</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="preprocessor">#ifndef CPU_ONLY</span></div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;  <span class="keywordflow">if</span> (Caffe::mode() == Caffe::GPU) {</div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;    CUDA_CHECK(cudaMallocHost(ptr, size));</div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;    *use_cuda = <span class="keyword">true</span>;</div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;    <span class="keywordflow">return</span>;</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;  }</div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="preprocessor">#endif</span></div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="preprocessor">#ifdef USE_MKL</span></div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;  *ptr = mkl_malloc(size ? size:1, 64);</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;<span class="preprocessor">#else</span></div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;  *ptr = malloc(size);</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;<span class="preprocessor">#endif</span></div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;  *use_cuda = <span class="keyword">false</span>;</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;  CHECK(*ptr) &lt;&lt; <span class="stringliteral">&quot;host allocation of size &quot;</span> &lt;&lt; size &lt;&lt; <span class="stringliteral">&quot; failed&quot;</span>;</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;}</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="keyword">inline</span> <span class="keywordtype">void</span> CaffeFreeHost(<span class="keywordtype">void</span>* ptr, <span class="keywordtype">bool</span> use_cuda) {</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;<span class="preprocessor">#ifndef CPU_ONLY</span></div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;  <span class="keywordflow">if</span> (use_cuda) {</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;    CUDA_CHECK(cudaFreeHost(ptr));</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;    <span class="keywordflow">return</span>;</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;  }</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<span class="preprocessor">#endif</span></div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;<span class="preprocessor">#ifdef USE_MKL</span></div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;  mkl_free(ptr);</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;<span class="preprocessor">#else</span></div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;  free(ptr);</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;<span class="preprocessor">#endif</span></div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;}</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;</div><div class="line"><a name="l00057"></a><span class="lineno"><a class="line" href="classcaffe_1_1SyncedMemory.html">   57</a></span>&#160;<span class="keyword">class </span><a class="code" href="classcaffe_1_1SyncedMemory.html">SyncedMemory</a> {</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;  <a class="code" href="classcaffe_1_1SyncedMemory.html">SyncedMemory</a>();</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;  <span class="keyword">explicit</span> <a class="code" href="classcaffe_1_1SyncedMemory.html">SyncedMemory</a>(<span class="keywordtype">size_t</span> size);</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;  ~<a class="code" href="classcaffe_1_1SyncedMemory.html">SyncedMemory</a>();</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">void</span>* cpu_data();</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;  <span class="keywordtype">void</span> set_cpu_data(<span class="keywordtype">void</span>* data);</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">void</span>* gpu_data();</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;  <span class="keywordtype">void</span> set_gpu_data(<span class="keywordtype">void</span>* data);</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;  <span class="keywordtype">void</span>* mutable_cpu_data();</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;  <span class="keywordtype">void</span>* mutable_gpu_data();</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;  <span class="keyword">enum</span> SyncedHead { UNINITIALIZED, HEAD_AT_CPU, HEAD_AT_GPU, SYNCED };</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;  SyncedHead head() { <span class="keywordflow">return</span> head_; }</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;  <span class="keywordtype">size_t</span> size() { <span class="keywordflow">return</span> size_; }</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;<span class="preprocessor">#ifndef CPU_ONLY</span></div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;  <span class="keywordtype">void</span> async_gpu_push(<span class="keyword">const</span> cudaStream_t&amp; stream);</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;<span class="preprocessor">#endif</span></div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160; <span class="keyword">private</span>:</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;  <span class="keywordtype">void</span> check_device();</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;  <span class="keywordtype">void</span> to_cpu();</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;  <span class="keywordtype">void</span> to_gpu();</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;  <span class="keywordtype">void</span>* cpu_ptr_;</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;  <span class="keywordtype">void</span>* gpu_ptr_;</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;  <span class="keywordtype">size_t</span> size_;</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;  SyncedHead head_;</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;  <span class="keywordtype">bool</span> own_cpu_data_;</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;  <span class="keywordtype">bool</span> cpu_malloc_use_cuda_;</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;  <span class="keywordtype">bool</span> own_gpu_data_;</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;  <span class="keywordtype">int</span> device_;</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;  DISABLE_COPY_AND_ASSIGN(<a class="code" href="classcaffe_1_1SyncedMemory.html">SyncedMemory</a>);</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;};  <span class="comment">// class SyncedMemory</span></div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;}  <span class="comment">// namespace caffe</span></div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;<span class="preprocessor">#endif  // CAFFE_SYNCEDMEM_HPP_</span></div><div class="ttc" id="namespacecaffe_html"><div class="ttname"><a href="namespacecaffe.html">caffe</a></div><div class="ttdoc">A layer factory that allows one to register layers. During runtime, registered layers can be called b...</div><div class="ttdef"><b>Definition:</b> blob.hpp:14</div></div>
<div class="ttc" id="classcaffe_1_1SyncedMemory_html"><div class="ttname"><a href="classcaffe_1_1SyncedMemory.html">caffe::SyncedMemory</a></div><div class="ttdoc">Manages memory allocation and synchronization between the host (CPU) and device (GPU). </div><div class="ttdef"><b>Definition:</b> syncedmem.hpp:57</div></div>
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